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I disagree with labeling AI to be a cargo cult. Crypto fits the description but the definition of a cargo cult has to imply some sort of ultimate end in which its follower's expectations are drastically reduced.

What AI feels like is the early days of the internet. We've seen the dot com bubble but we ultimately live in the internet age. There is no doubt that post-AI bubble will be very much AI orientated.

This is very different from crypto which isn't by any measure a technological leap rather more than a crowd frenzy aimed at self-enrichment via ponzi mechanisms.


I've been starting to think of it like this:

Great Engineer + AI = Great Engineer++ (Where a great engineer isn't just someone who is a great coder, they also are a great communicator & collaborator, and love to learn)

Good Engineer + AI = Good Engineer

OK Engineer + AI = Mediocre Engineer


I recently watched a mid-level engineer use AI to summarize some our code, and he had it put together a big document describing all the various methods in a file, what they're used for, and so forth. It looked to me like a huge waste of time, as the code itself was already very readable (I say this as someone who recently joined the project), and the "documentation" the AI spit out wasn't that different than what you'd get just by running pydoc.

He took a couple days doing this, which was shocking to me. Such a waste of time that would have been better spent reading the code and improving any missing documentation - and most importantly asking teammates about necessary context that couldn't just be inferred from the code.


I hate to break it to you, but this guy probably wasn’t working at all. That sounds like a pretense to goof off.

Now I could believe an intern would do such a thing. I’ve seen a structural engineer intern spend four weeks creating a finite element model of a single concrete vault. he could have treated the top deck as a concrete beam used conservative assumptions about the loading and solved it with pen and paper in 30 minutes.


Well, said engineer is no longer working at my company. He wasn't exactly the best developer...


I sort of think of it in terms of self-deskilling.

If an OK engineer is still actively trying to learn, making mistakes, memorizing essentials, etc. then there is no issue.

On the other hand, if they're surrendering 100% of their judgment to AI, then they will be mediocre.


The same people who just copy-pasted stack overflow answers and didn't understand why or how things work are now using AI to create stuff that they also don't understand.


And for low-stakes one-time hobby projects, they're correct to do so!


lol. I am SO glad I don't have to go to StackExchange anymore. There is something toxically awful about using advice from a thread that starts with "Why doesn't my code work?".


Is there a difference between "OK" and "Mediocre"?


“Ok” I generally associate with being adequate but could obviously be better. “Mediocre” is just inadequate.


Some synonyms for mediocre: decent, middling, ordinary, so-so. It can mean inadequate, but it can also mean adequate.


Another common synonym for mediocre: has no place on a software development team. Not technically correct, admittedly, but that's how I read that word in an software engineering context. Adequate is not good enough.


I’m just talking about how I view/use it.


“Mediocre” is one of those words where common parlance doesn’t quite line up with the textbook definition. e.g. from the Oxford English Dictionary: “Of middling quality; neither bad nor good...”


I probably should have written it as “OK Engineer--“


Not Engineer + AI = Now an Engineer

Thats the reason for high valuation of AI companies.


"Engineer" and "someone who can produce code" are not the same thing.


Of all the things I would absolutely not trust the stock market to evaluate, "technical competence" is either near or at the top.

The people deciding how much OpenAI is worth would probably struggle to run first-time setup on an iPad.


I agree. Seems like people took my comment above as my opinion. It was supposed to be argument of Linkedin type AI hype generators.


It seemed like a normative statement, to be honest, so I misunderstood your point.


Also, it was a time when being “online” was an active state. Now we’re “online” passively 24/7.


Yes, this is it. "Logging on" and "Logging off" were explicit actions that you took as part of your day, instead of just being perpetually connected and reachable.


The internet used to live in a room.


I love Monkeybrains! I had something in the neighborhood of a 600mbps symmetric connection through them in the late 2010s when I lived in SF. The only issue was when it rained hard the speeds would deteriorate.

Interesting you're getting such slow speeds. Ask them if a tech can stop by and troubleshoot with you.


I understand you're trying to "both sides" an argument. What have you found that has achieved for you in the past? Do you change people's opinions with this?


I have found that no amount of online discussion has ever changed anyone's mind on larger issues. We're all pissing in the wind here.


Then why did you post that?


I'm sure PaywallBuster has reviewed these and confirmed they were one-year spending before making their statement.


And then, The Charlie Rose Paradox: https://www.youtube.com/watch?v=iqW9sexNdZg


A step in the right direction last week for the largest upzoning effort in the city! https://archive.is/QuOcJ

Of course the a vocal minority is fuming about higher density.


Agreed, but I wonder--given investors demands for continued growth--if they're considering going up against NVIDIA.


Nah, surely 80% margins for matrix multiplication on the latest TSMC node will last forever.


It seems like you might be trying to use it like a search engine, which is a common mistake people make when first trying LLMs. LLMs are not like Google.

The key is to give it context so it can help you. For example, if you want it to help you with Spark configuration, give it the Spark docs. If you want it to help you write code, give it your codebase.

Tools like cursor and the like make this process very easy. You can also set up a local MCP server so the LLM can get the context and tools it needs on its own.


Thank you very much for the ideas here, i will try the approach of giving it context. I havent got into cursor, since i use helix and intellij… i need to look into the MCP server thing

Thanks again!


Giving examples of inputs and outputs can also help


thank you, I will try this too. I feel like I didn't have to do this much work with other models like o1/o3/4o... but if it provide the return value I'm hearing from the hype around Claude I am willing to try.


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